Rural institutions 203 07 06 mutual funds 294 11 15

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Rural institutions 20.3 23.0 1.0 1.0 0.7 0.6 Mutual funds 29.4 51.6 1.5 2.4 1.1 1.5 Venturecapital companies 2.7 2.3 0.1 0.1 0.1 0.1 Outstanding corporate bonds 62.8 61.5 3.3 3.0 2.2 1.8 Total \1863.9 2118.9 100 100.0 66.9 63.4 Equity market capitalization 801 1,249 n.a n.a 28.7 37.4 Source : Bapepam-LK, Bank Indonesia, Indonesia Stock Exchanges (IDX), 2006. Note: *GDP 2005:2,785.0 trillion and GDP 2006: 3,338.2 trillion 3. Methodology Framework and Data 3.1. Data Envelopment Analysis (DEA) The methodology used the Data Envelopment Analysis (DEA) approach to measure the relative performance of selected mutual funds in Indonesia. It is a suitable method to be used in this study as our sample size is small (Maghyereh, 2004; and Neal, 2004). Additionally, DEA is not vulnerable to the disproportion of small sample error as in the econometric model (Dogan and Fausten, 2003). We specifically uses the generalized output-oriented Malmquist index, developed by Fare et al. (1989) to measure the contribution from the progress in technology (technical change) and improvement in efficiency (efficiency change) to growth of productivity of the Indonesian mutual funds industries. The
58 Assessing Performance of Mutual Funds in Indonesia Malmquist indexes are constructed using the DEA and estimated using a program developed by Coelli (1996). Following Fare et al. (1989), the Malmquist productivity index is written as follows: 2 1 1 0 0 1 1 1 0 1 1 0 0 1 1 1 0 1 1 0 , , , , , , , , t t t t t t t t t t t t t t t t t t t t t t y x D y x D y x D y x D y x D y x D y x y x M (3.1) where the notations 1 1 0 , t t y x D , represents the distance from the period t+1 observation to the period t technology. The first ratio on the right hand side of the equation (3.1) measures the change in relative efficiency (i.e., the change in how far observed production is from the maximum potential production) between year t and t+1 . The second term inside the brackets (geometric mean of the two ratios) captures the shift in technology (i.e., movements of the frontier function itself) between the two periods evaluated at x t and x t+1 . That is, Efficiency Change = t t t t t t y x D y x D , , 0 1 1 1 0 (3.2) Technical Change = 2 1 1 0 1 0 1 1 1 0 1 1 0 , , , , t t t t t t t t t t t t y x D y x D y x D y x D (3.3) Essentially, the former investigates how well the production process converts inputs into outputs (catching up to the frontier) and the later reflects the improvement in technology. According to Fare et al. (1994), improvements in productivity yield Malmquist index values greater than unity. Deterioration in performance over time is associated with a Malmquist index less than unity. The same interpretation applies to the values taken by the components of the overall TFP index. An improvement in the efficiency component yield index values greater than one and is considered to be evidence of catching up (to the frontier). Values of the technical change component greater than one are

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